© 2015, fiatech increasing productivity through integrated dimensional change detection and control

© 2015, Fiatech

Increasing Productivity through Integrated

Dimensional Change Detection and Control 0.100m ~ 0.120m

0.080m ~ 0.100m

0.200m ~ 0.220m>0.220m

0.180m ~ 0.200m

Position change

BIM

Point cloud

© 2015, Fiatech

Presentation Flow

Presentation Takeaways/Deliverables

Opportunities Being Addressed

Constraints & Barriers

Approach & Benefits Realized

Future Work & Industry Adoption

Contact & More Information

Pres

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Flow

© 2015, FiatechPres

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Take

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• Importance of coordinating field dimensional changes and model changes

• Cost, safety, and productivity implications of changes

• Limitations of current methods of dimensional change management

• Methods for automating dimensional change analysis

• Potential value of automatic change analysis (ACA)

• Risks, barriers and further development

Owner

Contractor

DesignerVirtual World: Models

Physical World

Control

Data

Changes, deviations!

(Gordon et al., 2006)

© 2015, Fiatech

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Change Management and Productivity Problem:• Change management and verification is tedious

and error-prone, causing delays, wastes, and compromise performance

Challenges: • Interconnected dimensional changes• Interwoven objects in small spaces• “Cascading effects” of changes• Verification, validation, and avoidance of cost and

productivity impactsQuestions:• Which changes have higher impacts on the

downstream productivity and costs? • Which changes are more risky?• Could we anticipate changes?

(vision-systems.com)

© 2015, Fiatech

Existing Change Analysis ToolsCurrent Approach:• Automatic data-model registration• Automatic comparing “nearest neighbors”

in images and as-designed models to get “deviation maps”

Limitations:• Incorrect data-model associations• Requires extensive engineering resources

to manually review and classify changes • Difficult to anticipate how local

deformations interact to drive global displacements

Cons

trai

nts

& B

arrie

rs

(Turkan, Bosche, & Haas, 2010)

© 2015, Fiatech

Overcoming Incorrect Data-Model AssociationsProblem:• Matching data against model: which parts

in data and model have similar spatial contexts?

Spatial Context Matching:• Spatial relationships with neighboring

objects• Spatial contexts change less than absolute

geometriesVerification Study:• Preliminary studies prove the

effectiveness of spatial context matching on real data and model of ductworks

Appr

oach

& B

enefi

ts R

ealiz

ed

X

Y

Z

Duct 6

Duct 3

Duct 4

Duct 1

Duct 2

Duct 5

Context of duct 5: • Above four ducts• Intersecting with a duct• Parallel to two ducts• Perpendicular to three ducts

© 2015, Fiatech

Automated Change Classification Approach

• Different spatial changes cause different patterns in spatial deviations

• Use computer vision algorithms to classify patterns of spatial deviations

Appr

oach

& B

enefi

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ed

Spatial Change

Correspondence

Position Change

Dislocation Rotation

Shape Change

Elongation/

ShorteningCross-

Section Expanding/Shrinking

Concave/Convex

Missing Objects

Additional Objects

Wall rotation error

Building wing orientation error

© 2015, Fiatech

Automatically Recognizing How Local Dimensional Changes will Impact Global Displacements

• Data-model association• Align data parts against models parts, and

obtain translation, rotation values• “Lock-in” registered data and model parts

for local dimensional change analysis• Clustering dimensional changes that occur

together and locate in proximity• Identify combinations of changes that

occur in many cases as “change patterns”• Follow the paths of change propagation• Anticipate potential rework and cost

related to changes

Appr

oach

& B

enefi

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ealiz

ed

SEG 2 (0.12)

SEG 3 (-0.05)

SEG 1 (0)SEG 6 (0.06)

SEG 14 (-0.06)

SEG 4 (-0.04)

SEG 9 (-0.09)

SEG 8 (-0.21)

SEG 11 (-0.14)

SEG 5 (-0.06)

SEG 7 (-0.05)

SEG 12 (-0.08)

SEG 10 (0.05)

SEG 13 (-0.13)

JOINT 5

JOINT 2

JOINT 4

JOINT 9

© 2015, Fiatech

Automatic Change Analysis (ACA): Underway

• Large-scale testing of data-model association and change detection methods

• Developing more reliable change classification algorithms

• Developing robust “local” registration method for separating local and global changes

• Quantifying “cascading effects” of changes in terms of productivity and costs

• Leverage laser-based measurement technologies

Futu

re W

ork

& In

dust

ry A

dopti

on

Data-Model Association

Spatial Change Classification

Spatial Change Correlation

• Segmentation of 3D data• Geometric primitive extraction• Local spatial context generation• Local spatial context matching

• Spatial change taxonomy• 3D pattern classification

• Spatial change clustering• Statistical correlation analysis

Outputs• Relational graphs extracted from data and

the as-designed model• Spatial contexts of each object (duct) in the

data and the as-designed model• Matches between data and a-designed

objects

Outputs• Classified changes

Duct 1

Duct 2

Duct 3

Duct 4

Duct 5

Duct 6

Parallel

Perpendicular

PerpendicularPerpendicular

Parallel

Perpendicular

Perpendicular

Parallel

Perpendicular

© 2015, Fiatech

Industry Adoption: ProposedDefine and launch a Fiatech project:• Capitalize on a $0.5M NSF research grant• Interviews and surveys for potential barriers

of adopting automatic change analysis• Pilot studies: field data collection along with

relevant productivity and cost data of projects

• Cost-benefit analysis based on pilot studies• Diversifying the types of projects: building

construction, civil infrastructures• User-interface design: help from human-

computer interface scientists & engineers

Futu

re W

ork

& In

dust

ry A

dopti

on

Data-Model Association

Spatial Change Classification

Spatial Change Correlation

• Segmentation of 3D data• Geometric primitive extraction• Local spatial context generation• Local spatial context matching

• Spatial change taxonomy• 3D pattern classification

• Spatial change clustering• Statistical correlation analysis

Outputs• Relational graphs extracted from data and

the as-designed model• Spatial contexts of each object (duct) in the

data and the as-designed model• Matches between data and a-designed

objects

Outputs• Classified changes

Duct 1

Duct 2

Duct 3

Duct 4

Duct 5

Duct 6

Parallel

Perpendicular

PerpendicularPerpendicular

Parallel

Perpendicular

Perpendicular

Parallel

Perpendicular

© 2015, Fiatech

Thank You… Are There Any Questions?

Name: Pingbo TangTitle: Assistant ProfessorCompany: Arizona State UniversityEmail: [email protected] Links: https://sites.google.com/site/tangpingbo/ Office: 480-727-8105Fax: 480-965-1769

Cont

act &

Mor

e In

form

ation

Increasing Productivity through Integrated

Dimensional Change Detection and Control

mailto:[email protected]

https://sites.google.com/site/tangpingbo/

https://sites.google.com/site/tangpingbo/

© 2015, Fiatech

Increasing Design Efficiency

© 2015, Fiatech

Increasing Design Efficiency







Pres

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Flow


enta

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Take

away

s/D

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GENERATIVE DESIGN


enta

tion

Take

away

s/D

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les

Key Topics & Takeaways

1. Paradox of design2. Lean design technique – Set-Based Design3. Choice overload4. Application of the Generative Design PROCESS

© 2015, Fiatech

Presentation Flow







Pres

enta

tion

Flow

© 2015, Fiatech

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ortu

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Addr

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54%

© 2015, Fiatech

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Title in Calibri 32pt

© 2015, Fiatech

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WASTE

© 2015, Fiatech

Opp

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Paradox of DesignWe can’t make correct

decisions without knowing what the results will be…

…You can’t know the results without making decisions.

© 2015, Fiatech

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Paradox of Design

Design Validation

© 2015, Fiatech

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Stop ValidatingStart Simulating

Break the Paradox

© 2015, Fiatech

Presentation Flow







Pres

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tion

Flow

© 2015, Fiatech

Linear Design ProcessCo

nstr

aint

s &

Bar

riers

Collect Info.

Revise Decisions

Develop Design

VALIDATE one option

Make INTUITIVE Decision

1 2 3 4 5

RE-WORK

Multiple Iterations, minimal data

© 2015, Fiatech

Cons

trai

nts

& B

arrie

rs

How to Lean Design?

© 2015, Fiatech

Set-Based Design (SBD)Co

nstr

aint

s &

Bar

riers

Shape / massing

Orientation

Structural System

Envelope Systems

Lighting System

HVAC System

SINGLE SET

© 2015, Fiatech

Cons

trai

nts

& B

arrie

rs

3

+ 3

+ 3

+ 3

+ 3

+ 3

Shape / massing

Orientation

Structural System

Envelope Systems

Lighting System

HVAC System

SINGLE SET

SBD – Technical Challenge

© 2015, Fiatech

Cons

trai

nts

& B

arrie

rs

3

x 3

x 3

x 3

x 3

x 3

Shape / massing

Orientation

Structural System

Envelope Systems

Lighting System

HVAC System

= 729

SBD – Technical Challenge

© 2015, Fiatech

SBD – Technical ChallengeCo

nstr

aint

s &

Bar

riers

3 = 3

3 x 3 = 9

9 x 3 = 27

27 x 3 = 81

81 x 3 = 243

243 x 3 = 729

Shape / massing

Orientation

Structural System

Envelope Systems

Lighting System

HVAC System

© 2015, Fiatech

What if?Co

nstr

aint

s &

Bar

riers

Image courtesy of Beck Technologies

© 2015, Fiatech

SBD – Behavioral ChallengeCo

nstr

aint

s &

Bar

riers

CHOICE OVERLOAD

© 2015, Fiatech

Cons

trai

nts

& B

arrie

rs

30% 3%

SBD – Behavioral Challenge

© 2015, Fiatech

Set Based Design ChallengesCo

nstr

aint

s &

Bar

riers

Need to simulate more optionsHOWEVER

More options lead to difficult decision making

© 2015, Fiatech







Pres

enta

tion

Flow

Presentation Flow

© 2015, Fiatech

Linear Design ProcessAp

proa

ch &

Ben

efits

Rea

lized

Collect Info.

Revise Decisions

Develop Design

VALIDATE one option

Make INTUITIVE Decision

1 2 3 4 5

RE-WORK

Multiple Iterations, minimal data

© 2015, Fiatech

Rapid Virtual PrototypingAp

proa

ch &

Ben

efits

Rea

lized

Collect Info.

Simulate & Analyze

Develop ONE time

Make INFORMED

Decision

1 32

4Next

Decision Set

ONE iteration, more data

Simulate & Analyze

2

Simulate & Analyze

2

Multiple data sets

© 2015, Fiatech

AEC Application: Rapid Trade-off AnalysisAp

proa

ch &

Ben

efits

Rea

lized First cost

vs. Life-cycle energy

1

© 2015, Fiatech

Simulation ToolkitAp

proa

ch &

Ben

efits

Rea

lized

MODELENER

GY COSTImage courtesy of Sefaira

2

© 2015, Fiatech

Collect Glazing InformationAp

proa

ch &

Ben

efits

Rea

lized

~60 min

2

© 2015, Fiatech

Tools: ModelingAp

proa

ch &

Ben

efits

Rea

lized

~45 min

2

© 2015, Fiatech

Rapid Energy SimulationAp

proa

ch &

Ben

efits

Rea

lized

~60 min

2

© 2015, Fiatech

Data AggregationAp

proa

ch &

Ben

efits

Rea

lized

~15 min

2

© 2015, Fiatech

Graphic AnalysisAp

proa

ch &

Ben

efits

Rea

lized

~90 min

2

© 2015, Fiatech

Simulation AnalysisAp

proa

ch &

Ben

efits

Rea

lized

2

36 glazing options1 scheme4.5 hours

© 2015, Fiatech

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ortu

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ing

Addr

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WASTE

© 2015, Fiatech







Pres

enta

tion

Flow

Presentation Flow

© 2015, Fiatech

Solution to SBD ChallengesAp

proa

ch &

Ben

efits

Rea

lized

Outside the

AEC Box

© 2015, Fiatech

Penn State Applied Research LabAp

proa

ch &

Ben

efits

Rea

lized

Image courtesy of Penn State Applied Research Lab

© 2015, Fiatech

Jet Propulsion Laboratory (JPL)Ap

proa

ch &

Ben

efits

Rea

lized

© 2015, Fiatech

Appr

oach

& B

enefi

ts R

ealiz

ed

VTCC Case Study: Cost Optimization

© 2015, Fiatech

VTCC Case Study: East FacadeAp

proa

ch &

Ben

efits

Rea

lized

© 2015, Fiatech

Appr

oach

& B

enefi

ts R

ealiz

ed

Potential of Removing the Rework Loop

Team = 6-7 people @ $120/hr

Average of 40 hours each= $33,600

© 2015, Fiatech

Appr

oach

& B

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Methodology Benefits

Cut design duration in half or more?Solve more problems in the same time?

Do more with less?

© 2015, Fiatech

Process ChangeFu

ture

Wor

k &

Indu

stry

Ado

ption

Develop many solutions Analyze options

Prioritize decisions

© 2015, Fiatech


Jason A. ReeceTechnology Innovation & ImprovementBalfour Beatty [email protected]/in/jar321

Cont

act &

Mor

e In

form

ation Increasing Design

Efficiency

© 2015, Fiatech

Knowledge Mining: Experience Capture & Sharing

- Not important – Who cares??- Coming Soon to a Project Near You??- Utopian Dream??- Distant Future??

© 2015, Fiatech

Presentation Flow

Construction’s Incredible Knowledge Intensity

Where Knowledge Lives

Mating: How Problems Find Knowledge

Possible Approach & Benefits Realized

Barriers

Contact info

Pres

enta

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Flow

© 2015, Fiatech

Pres

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Take

away

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Extraordinary Density of Embedded Knowledge

• Not obvious to those at arm’s length

• Complexity reduced in a well-defined system

• Each material has its own complexities

• Each interface between materials • Requires situation-specific knowledge • Small ignorance may = big problem

• Procedural vs. situational knowledge• Bid system adds cost optimization to the

knowledge embedded in a particular prototype

© 2015, Fiatech

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How do problems meet up with knowledge?

• IF the problem is common & mastered• Then it’s not a problem anymore

• IF the problem is highly specific Then • Narrow specialists with knowledge or• Bungled task (partly or fully)

• To avoid problem (e.g. at left) • Find and read an academic paper?• Search online (and pay for info?)?• Use a deep specialist

• Informally transmit knowledge collegially

• How can more people learn from others?

© 2015, Fiatech

Benefits and Possible Approach• Effective sharing of knowledge => reduced

project costs and risks.

• Software (non-trivial) + social change (very very large challenge) is required

• Must engage and incentivize knowledge holders (big challenge).

• Users must engage and love using it

• Involve many trade associations (are incumbent orgs. “owning” knowledge)

• Find various interested companies

• Create a committed eco-system

Cons

trai

nts

& B

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rs

© 2015, Fiatech

Barriers In ascending order of importance:

• Legal – fully indemnify contributors

• $ Cost to create software and participation

• Needs exquisitely usable software

• Maintenance of data

• Get a wide range of committed sponsors

• Vetting of contributions and contributors

• Getting contributors

• Getting users

• Getting Creating the virtuous circle of use and contribution (Wikipedia and eBay, sim.)

Appr

oach

& B

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ed

© 2015, Fiatech


Leo SchlosbergCary Concrete Products, Inc. Email: [email protected]: www.caryconcrete.comBlog: www.planetcommercialconstruction.wordpress.com

An earlier and more detailed version of this presentationcan be found at: http://www.caryconcrete.com/writings/index.php?page=writings

Cont

act &

Mor

e In

form

ation Sharing knowledge

http://www.planetcommercialconstruction.wordpress.com/

http://www.caryconcrete.com/writings/index.php?page=writings

© 2015, Fiatech

Integrated Design Practices

Objective:To provide clarity on the process to document the Information Specifications Management strategy to meet & exceed Customer “Data Centric” project Information Handover Specification requirements.

• What systems are being utilised?• What data is being produced, consumed,

reused and turned over?• What are the applicable data standards? • What are the applicable data QA &

validation rules?

© 2015, Fiatech

Presentation Flow

Information Governance – Class Library

Standards Driven – Data Management

Project & Customer specific Class Library Management




Pres

enta

tion

Flow

© 2015, FiatechInfo

rmati

on G

over

nanc

e –

Clas

s Li

brar

y

Engineering Data Warehouse (EDW)

Information Governance – Class Library

Tag and Document Numbering Specifications

Customer ‘Data Centric’ Information Handover Spec.

Industry Standards i.e. ISO 15926, BIM etc.

Data Validation Rules

Customer and Project Specific Configuration

Project Delivery Systems

© 2015, FiatechStan

dard

s D

riven

– D

ata

Man

agem

ent

Data Validation Rules (Standards Conformance)

Customer specific ‘Data Centric’ information handover specifications

WorleyParsons Standard Class Library

Stan

dard

Del

ivery

Con

figur

atio

n

Engineering Data Warehouse (EDW)(Consolidated & Validated) Pr

ojec

t & C

usto

mer

spe

cific

Conf

igur

atio

n

Customer Specified Configuration

Project Delivery Systems(Authoring Applications)

Tag & Document No. SpecificationsNaming Rules

Functional / Physical Classes & AttributesValidation RulesLife Cycle Rules

Industry Standard MappingsAuthoring Application Data Mappings

Class LibraryTag & Document No. Specifications Information Handover Specification

Validation RulesIndustry Standards

Publish & Compare

© 2015, Fiatech

Proj

ect &

Cus

tom

er s

peci

fic C

lass

Lib

rary

Man

agem

ent

Customer specific ‘Data Centric’ Information Handover

Electrical

EDMS

Customer/Project

Specific

Class Library(Layer 3)

Project

Configuration

SupplierContent

Project

Configuration

3D Modeling

Project

Configuration

Project

Configuration

Inst. & Control

Project

Configuration

P&IDProject

Configuration

Mechanical

Datasheets

Project

Configuration

MTR

Engineering Data Warehouse

Project

Configuration

Electrical

EDMSProject

Configuration

SupplierContent

Project

Configuration

3D Modeling

Project

Configuration

Project

Configuration

Inst. & Control

Project

Configuration

P&IDProject

Configuration

Mechanical

Datasheets

Project

Configuration

MTR

Engineering Data WarehouseGoal: To meet & exceed Customer information handover expectations

Project

Configuration

Project Specific Configuration

ProjectSpecific


ProjectSpecific


CustomerSpecific


Tag, Document

NamingStandards(Layer 0)

Industry Standards

i.e. ISO 15926(Layer 0)

WorleyParsons

Standard Class

Library(Layer 0)

© 2015, Fiatech

Appr

oach

& B

enefi

ts R

ealiz

ed

Physical ClassesNo. of Physical Attributes

mapped to Project Delivery Systems.

Functional Document Types

No. of Functional Document Types Mapped.

ISO 15926 StandardNo. of Physical Attributes

mapped to ISO 15926 RDL

Engineering Data Warehouse

No. of integrated Project Delivery Systems mapped to

Class Library

ISO 15926 StandardNo. of Functional Classes

mapped to ISO 15926 RDL in Class Library

Units of Measure Classes

No. of Units of Measure Classes

39%156

435%

11

200

55

Life Cycle TypesNo. of Life Cycle data types across Define, Execute and

Operate phases.

10

Functional AttributesNo. of Functional Attributes mapped to Project Delivery

Systems

400

Equipment Function Codes

No. of Equipment Function Codes Mapped (Excluding

Piping Line Numbers)

613

Instrument Function Codes

No. of ANSI/ISA Instrument Function Codes Mapped

391

Physical Document

TypesNo. of Physical Document

Types Mapped.

98

© 2015, Fiatech


Cormac RyanManager, Project Data [email protected]

Photo

Cont

act &

Mor

e In

form

ation Achieving Effective Information

Specifications Management

mailto:[email protected]

© 2015, fiatech increasing productivity through integrated dimensional change detection and control

Documents

matching data

local dimensional changes

model changescost

real data

registered data

changes difficult

spatial context matching

spatial relationships